51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
import os, sys
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src_dir = os.path.join(
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os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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)
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sys.path.append(src_dir)
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from configs import llm_model_dict, LLM_MODEL
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import openai
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# os.environ["OPENAI_PROXY"] = "socks5h://127.0.0.1:7890"
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# os.environ["OPENAI_PROXY"] = "http://127.0.0.1:7890"
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# os.environ["OPENAI_API_KEY"] = ""
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if __name__ == "__main__":
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# print("dsadsa", os.environ.get("OPENAI_PROXY"), os.environ.get("OPENAI_API_KEY"))
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from langchain import PromptTemplate, LLMChain
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from langchain.prompts.chat import ChatPromptTemplate
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from langchain.chat_models import ChatOpenAI
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from langchain.schema import HumanMessage
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# chat = ChatOpenAI(temperature=0.1, model_name="gpt-3.5-turbo")
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# print(chat.predict("hi!"))
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# print(LLM_MODEL, llm_model_dict[LLM_MODEL]["api_key"], llm_model_dict[LLM_MODEL]["api_base_url"])
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# model = ChatOpenAI(
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# streaming=True,
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# verbose=True,
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# openai_api_key=llm_model_dict[LLM_MODEL]["api_key"],
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# openai_api_base=llm_model_dict[LLM_MODEL]["api_base_url"],
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# model_name=LLM_MODEL
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# )
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# chat_prompt = ChatPromptTemplate.from_messages([("human", "{input}")])
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# chain = LLMChain(prompt=chat_prompt, llm=model)
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# content = chain({"input": "hello"})
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# print(content)
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import openai
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# openai.api_key = "EMPTY" # Not support yet
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openai.api_base = "http://127.0.0.1:8888/v1"
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model = "example"
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# create a chat completion
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completion = openai.ChatCompletion.create(
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model=model,
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messages=[{"role": "user", "content": "Hello! What is your name? "}],
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max_tokens=100,
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)
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# print the completion
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print(completion.choices[0].message.content) |